#网友投稿:这部大皮卡就是联合国DU品和犯罪问题办公室(UNODC)办事处的车辆。 该机构常驻柬埔寨,办事点设在金边,主要协助当地打击电信诈骗、人口贩运、DU品等跨国犯罪,本次派员到场观摩这场执法行动。 不过他们在柬埔寨没有执法权,不能抓人、查封场所,只负责提供技术支持、调研见证以及相关业务培训。 👌👌👌👌👌👌👌 内涵素材频道 @vdddd 海外素材频道 @dj488 广告投放联系 @dadi958 关注全球大事件频道 @vip9pppp
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Channel
@vip9pppp
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Handles named that no longer answer · Cite this entry
44,265subscribers
-28,145 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001970303468 |
|---|---|
| Type | Channel |
| Username | @vip9pppp |
| Created | Between 1 April 2023 and 31 October 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 14 October 2026 |
| Measurements held | 38 |
| Confirmed unchanged | 1 time, most recently 14 October 2026 |
| On Telegram | t.me/vip9pppp |
National news — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 44% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 14 Oct 2026, 22:51 | 44,265 | -49 |
| 13 Oct 2026, 18:27 | 44,314 | -222 |
| 9 Oct 2026, 23:59 | 44,536 | -365 |
| 5 Oct 2026, 17:01 | 44,901 | -706 |
| 30 Sept 2026, 05:39 | 45,607 | -665 |
| 18 Sept 2026, 05:21 | 46,272 | -107 |
| 15 Sept 2026, 23:39 | 46,379 | -68 |
| 14 Sept 2026, 03:42 | 46,447 | -92 |
| 12 Sept 2026, 08:00 | 46,539 | -204 |
| 10 Sept 2026, 05:36 | 46,743 | -510 |
| 6 Sept 2026, 20:38 | 47,253 | -197 |
| 4 Sept 2026, 04:39 | 47,450 | -95 |
| 2 Sept 2026, 15:53 | 47,545 | -85 |
| 1 Sept 2026, 18:24 | 47,630 | -136 |
| 31 Aug 2026, 20:48 | 47,766 | -69 |
| 30 Aug 2026, 20:47 | 47,835 | -286 |
| 29 Aug 2026, 19:35 | 48,121 | -1,971 |
| 28 Aug 2026, 16:12 | 50,092 | -377 |
| 27 Aug 2026, 19:26 | 50,469 | -206 |
| 26 Aug 2026, 21:14 | 50,675 | first reading |
1,758 posts held, back to 6 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 138 pages of Telegram’s post history, 20 posts per page.
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 716 of 727 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 14 October 2026 |
|---|---|
| Posts held | 1,758 (6 August 2026 – 14 October 2026) |
| Views total | 3,904,871 |
| Reactions total | 16,493 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 14 Oct 2026, 21:07 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
Measured directly from 260 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
20,153 reactions across 882 posts, in 12 distinct kinds. The most used accounts for 11.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2,307 | 11.4% | |
| 🤩 | 2,275 | 11.3% | |
| 💯 | 2,263 | 11.2% | |
| 👍 | 2,256 | 11.2% | |
| ❤🔥 | 2,238 | 11.1% | |
| 😍 | 2,216 | 11.0% | |
| 🎉 | 2,213 | 11.0% | |
| 🥰 | 2,188 | 10.9% | |
| 🔥 | 2,174 | 10.8% | |
| 😁 | 9 | 0.045% | |
| ⚡ | 8 | 0.04% | |
| 👏 | 6 | 0.03% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 882 of the 1,000 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 20,153 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 5 September 2026 to 14 October 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
#网友投稿:这部大皮卡就是联合国DU品和犯罪问题办公室(UNODC)办事处的车辆。 该机构常驻柬埔寨,办事点设在金边,主要协助当地打击电信诈骗、人口贩运、DU品等跨国犯罪,本次派员到场观摩这场执法行动。 不过他们在柬埔寨没有执法权,不能抓人、查封场所,只负责提供技术支持、调研见证以及相关业务培训。 👌👌👌👌👌👌👌 内涵素材频道 @vdddd 海外素材频道 @dj488 广告投放联系 @dadi958 关注全球大事件频道 @vip9pppp
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柬埔寨内政部回应半岛电视台纪录片:坚决否认保护伞质疑 针对半岛电视台纪录片揭露七星海长湾诈骗园区及华裔商人邓丕兵声称“八成收益用于打点关系”一事,柬埔寨内政部副发言人杜速克回应称,这纯属邓丕兵个人夸大事实、炫耀背景的吹嘘行为,绝无政府机构或官员与其分红。 关于视频中出现的警车,杜速克强调,政府严禁公车私用或为非法活动打掩护,不排除私自改装或假冒警车的可能。 针对涉案的“长湾”园区,内政部证实警方此前已对其展开行政检查与打击封锁,目前案件正依法深挖,坚决打击利用国家资源与合法投资掩盖非法勾当的行为。 👌👌👌👌👌👌👌 内涵素材频道 @vdddd 海外素材频道 @dj488 广告投放联系 @dadi958 关注全球大事件频道 @vip9pppp
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Photo, posted without a caption
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柬埔寨内政部回应半岛电视台纪录片:坚决否认保护伞质疑 针对半岛电视台纪录片揭露七星海长湾诈骗园区及华裔商人邓丕兵声称“八成收益用于打点关系”一事,柬埔寨内政部副发言人杜速克回应称,这纯属邓丕兵个人夸大事实、炫耀背景的吹嘘行为,绝无政府机构或官员与其分红。 关于视频中出现的警车,杜速克强调,政府严禁公车私用或为非法活动打掩护,不排除私自改装或假冒警车的可能。 针对涉案的“长湾”园区,内政部证实警方此前已对其展开行政检查与打击封锁,目前案件正依法深挖,坚决打击利用国家资源与合法投资掩盖非法勾当的行为。 👌👌👌👌👌👌👌 内涵素材频道 @vdddd 海外素材频道 @dj488 广告投放联系 @dadi958 关注全球大事件频道 @vip9pppp
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#最新消息:西港“赢嘉赌场”里的柬埔寨员工已经撤出去了,留给执法部门进去调查。 👌👌👌👌👌👌👌 内涵素材频道 @vdddd 海外素材频道 @dj488 广告投放联系 @dadi958 关注全球大事件频道 @vip9pppp
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柬埔寨巴域N98 (3)号酒店疑涉大规模网络犯罪,另有房间被指存在吸DU行为 据报道,柬埔寨巴域市龙皮(Long Pi)地区的N98 (3)号旅馆/酒店疑似存在大规模非法网络犯罪活动。该地点靠近越南木牌(Moc Bai)边境口岸,距离主干道约700米。 据相关信息显示,涉嫌网络犯罪的活动范围涉及该建筑的6楼、7楼及8楼。此外,716号房间还被指存在吸DU行为。 目前,相关情况仍有待进一步核实,具体涉案人员数量及执法部门是否已采取行动,尚不明确。 👌👌👌👌👌👌👌 内涵素材频道 @vdddd 海外素材频道 @dj488 广告投放联系 @dadi958 关注全球大事件频道 @vip9pppp
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Showing the 12 most recent of 1,758 posts we hold for @vip9pppp. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
@vip9pppp edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
Named by 2 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
@vip9pppp named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
References a handle that is not a live channel — we have no record it ever was one.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 14 October 2026 — this entry's latest reading, not the date you are reading this.
“全球华人大事件|重磅新闻|曝光|吃瓜🌏” (@vip9pppp), 44,265 subscribers as measured 14 October 2026. Telegram Register, tgregister.com/channel/vip9pppp.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.